Comments (2)
jstovold
commented on June 11, 2024
I've managed to fix the problem in my code, but there might still be an underlying issue in Spektral relating to it. I fixed it by creating the adjacency matrix as a coo_matrix instead of a coo_array.
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danielegrattarola
commented on June 11, 2024
Yeah I haven't seen that coo_array type before and Spektral assumes a COO matrix, but I'll look into extending support.
Thanks for raising this
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Related Issues (20)
- Issue with using pooling layers in Spektral package for graph neural networks HOT 1
- Issue with shapes after saving and loading the model HOT 1
- Create custom Graph Extension Type HOT 3
- No gradient for the initial adjacency matrix with TopKPooling HOT 3
- Input shape for the GraphSAGE layer and sparse tensor construction
- Adding the Edges in GIN model HOT 1
- Adding the DGIN convolution ?
- Adding D-MPNNConv
- Inquiry about the usability of graph classification HOT 1
- How to evaluate a graph regression model with new data? HOT 4
- Problem using GNNExplainer HOT 4
- Dependency Issue on Mac M2 Pro HOT 2
- model.evalute() reprodusibility problem HOT 5
- Columns and DataType Not Explicitly Set on line 55 of io.py
- load data to fit the model (Spektral & Keras) HOT 2
- Is it require to create an adjacency matrix? HOT 2
- 'GATConv' object is not callable
- How to use Single Mode when I am training for the same graph structure HOT 1
- How to match real label with predicted y after using model.predict() with disjointloader? HOT 2
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